Aflibercept Off-Target Effects in Diabetic Macular Edema: An In Silico Modeling Approach.

Intravitreal aflibercept injection (IAI) is a treatment for diabetic macular edema (DME), but its mechanism of action (MoA) has not been completely elucidated. Here, we aimed to explore IAI's MoA and its multi-target nature in DME pathophysiology with an in silico (computer simulation) disease model. We used the Therapeutic Performance Mapping System (Anaxomics Biotech property) to generate mathematical models based on the available scientific knowledge at the time of the study, describing the relationship between the modulation of vascular endothelial growth factor receptors (VEGFRs) by IAI and DME pathophysiological processes. We also undertook an enrichment analysis to explore the processes modulated by IAI, visualized the effectors' predicted protein activity, and specifically evaluated the role of VEGFR1 pathway inhibition on DME treatment. The models simulated the potential pathophysiology of DME and the likely IAI's MoA by inhibiting VEGFR1 and VEGFR2 signaling. The action of IAI through both signaling pathways modulated the identified pathophysiological processes associated with DME, with the strongest effects in angiogenesis, blood-retinal barrier alteration and permeability, and inflammation. VEGFR1 inhibition was essential to modulate inflammatory protein effectors. Given the role of VEGFR1 signaling on the modulation of inflammatory-related pathways, IAI may offer therapeutic advantages for DME through sustained VEGFR1 pathway inhibition.

Generation of Self-Induced Myocardial Ischemia in Large-Sized Cardiac Spheroids without Alteration of Environmental Conditions Recreates Fibrotic Remodeling and Tissue Stiffening Revealed by Constriction Assays.

A combination of human-induced pluripotent stem cells (hiPSCs) and 3D microtissue culture techniques allows the generation of models that recapitulate the cardiac microenvironment for preclinical research of new treatments. In particular, spheroids represent the simplest approach to culture cells in 3D and generate gradients of cellular access to the media, mimicking the effects of an ischemic event. However, previous models required incubation under low oxygen conditions or deprived nutrient media to recreate ischemia. Here, we describe the generation of large spheroids (i.e., larger than 500 µm diameter) that self-induce an ischemic core. Spheroids were generated by coculture of cardiomyocytes derived from hiPSCs (hiPSC-CMs) and primary human cardiac fibroblast (hCF). In the proper medium, cells formed aggregates that generated an ischemic core 2 days after seeding. Spheroids also showed spontaneous cellular reorganization after 10 days, with hiPSC-CMs located at the center and surrounded by hCFs. This led to an increase in microtissue stiffness, characterized by the implementation of a constriction assay. All in all, these phenomena are hints of the fibrotic tissue remodeling secondary to a cardiac ischemic event, thus demonstrating the suitability of these spheroids for the modeling of human cardiac ischemia and its potential application for new treatments and drug research.

An in silico approach to identify early damage biomarker candidates in metachromatic leukodystrophy.

Metachromatic leukodystrophy (MLD) is a rare, autosomal recessive lysosomal storage disease. Deficient activity of arylsulfatase A causes sulfatides to accumulate in cells of different tissues, including those in the central and peripheral nervous systems, leading to progressive demyelination and neurodegeneration. Although there is some association between specific arylsulfatase A alleles and disease severity, genotype-phenotype correlations are not fully understood. We aimed to identify biomarker candidates of early tissue damage in MLD using a modeling approach based on systems biology. A review of the literature was performed in an initial disease characterization step, allowing identification of pathophysiological processes involved in MLD and proteins relating to these processes. Three mathematical models were generated to simulate different stages of MLD at the molecular level: an early pro-inflammatory stage model (including only processes considered to be active in the early stages of disease), a pre-demyelination stage model (including additional processes that are active after some disease progression), and a demyelination stage model (in which all pathophysiological processes are active). The models evaluated 3457 proteins of interest, individually and by pairs through data mining techniques, applying five filters to prioritize biomarkers that could differentiate between the models. Sixteen potential biomarkers were identified, including effectors relating to mitochondrial dysfunction, remyelination, and neurodegeneration. The findings were corroborated in a gene expression data set from T lymphocytes of patients with MLD; all candidates formed combinations that were able to distinguish patients with MLD from controls, and all but one candidate distinguished late-infantile MLD from juvenile MLD as part of a combinatorial biomarker pair. In particular, pro-neuregulin-1 appeared as differential on all comparisons (patients with MLD vs controls and within clinical subtypes); casein kinase II subunit alpha was detected as a potential individual marker within clinical subtypes. These findings provide a panel of biomarker candidates suitable for experimental validation and highlight the utility of mathematical models to identify biomarker candidates of early tissue damage in MLD with a high degree of accuracy and sensitivity.

Application of systems biology to identify pharmacological mechanisms of thrombotic microangiopathy evoked by combined activated prothrombin complex concentrate and emicizumab.

Emicizumab is a bispecific monoclonal antibody that substitutes for the function of missing or deficient factor VIII (FVIII) in people with hemophilia A (PwHA). Long-term safety and efficacy of emicizumab have been demonstrated in several clinical trials. Nevertheless, in the first of these, three cases of thrombotic microangiopathy (TMA) occurred in PwHA treated with emicizumab receiving high doses of activated prothrombin complex concentrate (aPCC), a bypassing agent used for treating breakthrough bleeds when FVIII neutralizing antibodies (inhibitors) make FVIII replacement ineffective. The aim of the present work is to offer a method to elucidate the pathophysiological and pharmacological mechanisms involved in this treatment-induced TMA. Systems biology and machine learning-based Therapeutic Performance Mapping System is a validated in silico technology that allowed us to construct models of potential mechanisms behind induced TMA. Two drug combinations were modeled and assessed: emicizumab plus aPCC and emicizumab plus recombinant activated factor VII (another bypassing agent). Our models showed that both combinations were related to activation of the coagulation cascade. However, mechanisms involved mainly in platelet activation and possibly in complement activation were detected only for emicizumab plus aPCC, potentially explaining the occurrence of TMA only in this combination.

Artificial intelligence assessment of the potential of tocilizumab along with corticosteroids therapy for the management of COVID-19 evoked acute respiratory distress syndrome.

Acute respiratory distress syndrome (ARDS), associated with high mortality rate, affects up to 67% of hospitalized COVID-19 patients. Early evidence indicated that the pathogenesis of COVID-19 evoked ARDS is, at least partially, mediated by hyperinflammatory cytokine storm in which interleukin 6 (IL-6) plays an essential role. The corticosteroid dexamethasone is an effective treatment for severe COVID-19 related ARDS. However, trials of other immunomodulatory therapies, including anti-IL6 agents such as tocilizumab and sarilumab, have shown limited evidence of benefit as monotherapy. But recently published large trials have reported added benefit of tocilizumab in combination with dexamethasone in severe COVID-19 related ARDS. In silico tools can be useful to shed light on the mechanisms evoked by SARS-CoV-2 infection and of the potential therapeutic approaches. Therapeutic performance mapping system (TPMS), based on systems biology and artificial intelligence, integrate available biological, pharmacological and medical knowledge to create mathematical models of the disease. This technology was used to identify the pharmacological mechanism of dexamethasone, with or without tocilizumab, in the management of COVID-19 evoked ARDS. The results showed that while dexamethasone would be addressing a wider range of pathological processes with low intensity, tocilizumab might provide a more direct and intense effect upon the cytokine storm. Based on this in silico study, we conclude that the use of tocilizumab alongside dexamethasone is predicted to induce a synergistic effect in dampening inflammation and subsequent pathological processes, supporting the beneficial effect of the combined therapy in critically ill patients. Future research will allow identifying the ideal subpopulation of patients that would benefit better from this combined treatment.

Unveiling chronic spontaneous urticaria pathophysiology through systems biology.

BACKGROUND: Chronic spontaneous urticaria (CSU) is a rare, heterogeneous, severely debilitating, and often poorly controlled skin disease resulting in an itchy eruption that can be persistent. Antihistamines and omalizumab, an anti-IgE mAb, are the only licensed therapies. Although CSU pathogenesis is not yet fully understood, mast cell activation through the IgE:high-affinity IgE receptor (FcεRI) axis appears central to the disease process. OBJECTIVE: We sought to model CSU pathophysiology and identify in silico the mechanism of action of different CSU therapeutic strategies currently in use or under development. METHODS: Therapeutic performance mapping system technology, based on systems biology and machine learning, was used to create a CSU interactome validated with gene expression data from patients with CSU and a CSU model that was used to evaluate CSU pathophysiology and the mechanism of action of different therapeutic strategies. RESULTS: Our models reflect the known role of mast cell activation as a central process of CSU pathophysiology, as well as recognized roles for different therapeutic strategies in this and other innate and adaptive immune processes. They also allow determining similarities and differences between them; anti-IgE and Bruton tyrosine kinase inhibitors play a more direct role in mast cell biology through abrogation of FcεRI signaling activity, whereas anti-interleukins and anti-Siglec-8 have a role in adaptive immunity modulation. CONCLUSION: In silico CSU models reproduced known CSU and therapeutic strategies features. Our results could help advance understanding of therapeutic mechanisms of action and further advance treatment research by patient profile.

Current approaches for the recreation of cardiac ischaemic environment in vitro.

Myocardial ischaemia is one of the leading dead causes worldwide. Although animal experiments have historically provided a wealth of information, animal models are time and money consuming, and they usually miss typical human patient's characteristics associated with ischemia prevalence, including aging and comorbidities. Generating reliable in vitro models that recapitulate the human cardiac microenvironment during an ischaemic event can boost the development of new drugs and therapeutic strategies, as well as our understanding of the underlying cellular and molecular events, helping the optimization of therapeutic approaches prior to animal and clinical testing. Although several culture systems have emerged for the recreation of cardiac physiology, mimicking the features of an ischaemic heart tissue in vitro is challenging and certain aspects of the disease process remain poorly addressed. Here, current in vitro cardiac culture systems used for modelling cardiac ischaemia, from self-aggregated organoids to scaffold-based constructs and heart-on-chip platforms are described. The advantages of these models to recreate ischaemic hallmarks such as oxygen gradients, pathological alterations of mechanical strength or fibrotic responses are highlighted. The new models represent a step forward to be considered, but unfortunately, we are far away from recapitulating all complexity of the clinical situations.

Female Sex, Age, and Unfavorable Response to Tumor Necrosis Factor Inhibitors in Patients With Axial Spondyloarthritis: Results of Statistical and Artificial Intelligence-Based Data Analyses of a National Multicenter Prospective Registry.

OBJECTIVE: Real-world studies are needed to identify factors associated with response to biologic therapies in patients with axial spondyloarthritis (SpA). The objective was to assess sex differences in response to tumor necrosis factor inhibitors (TNFi) and to explore possible risk factors associated with TNFi efficacy. METHODS: A total of 969 patients with axial SpA (315 females, 654 males) enrolled in the BIOBADASER registry (2000-2019) who initiated a TNFi (first, second, or further lines) were studied. Statistical and artificial intelligence (AI)-based data analyses were used to explore the association of sex differences and other factors to TNFi response, using the Bath Ankylosing Spondylitis Disease Activity Index (BASDAI), to calculate the BASDAI50, with an improvement of at least 50% of the BASDAI score, and using the Ankylosing Spondylitis Disease Activity Score, calculated using the C-reactive protein level (ASDAS-CRP). RESULTS: Females had a lower probability of reaching a BASDAI50 response with a first line TNFi treatment at the second year of follow-up (P = 0.018) and a lesser reduction of the ASDAS-CRP at this time point. The logistic regression model showed lower BASDAI50 responses to TNFi in females (P = 0.05). Other factors, such as older age (P = 0.004), were associated with unfavorable responses. The AI data analyses reinforced the idea that age at the beginning of the treatment was the main factor associated with an unfavorable response. The combination of age with other clinical characteristics (female sex or cardiovascular risk factors and events) potentially contributed to an unfavorable response to TNFi. CONCLUSION: In this national multicenter registry, female sex was associated with less response to a first-line TNFi by the second year of follow-up. A higher age at the start of the TNFi was the main factor associated with an unfavorable response to TNFi.

Identification of the Potential Molecular Mechanisms Linking RUNX1 Activity with Nonalcoholic Fatty Liver Disease, by Means of Systems Biology.

Nonalcoholic fatty liver disease (NAFLD) is the most prevalent chronic hepatic disease; nevertheless, no definitive diagnostic method exists yet, apart from invasive liver biopsy, and nor is there a specific approved treatment. Runt-related transcription factor 1 (RUNX1) plays a major role in angiogenesis and inflammation; however, its link with NAFLD is unclear as controversial results have been reported. Thus, the objective of this work was to determine the proteins involved in the molecular mechanisms between RUNX1 and NAFLD, by means of systems biology. First, a mathematical model that simulates NAFLD pathophysiology was generated by analyzing Anaxomics databases and reviewing available scientific literature. Artificial neural networks established NAFLD pathophysiological processes functionally related to RUNX1: hepatic insulin resistance, lipotoxicity, and hepatic injury-liver fibrosis. Our study indicated that RUNX1 might have a high relationship with hepatic injury-liver fibrosis, and a medium relationship with lipotoxicity and insulin resistance motives. Additionally, we found five RUNX1-regulated proteins with a direct involvement in NAFLD motives, which were NFκB1, NFκB2, TNF, ADIPOQ, and IL-6. In conclusion, we suggested a relationship between RUNX1 and NAFLD since RUNX1 seems to regulate NAFLD molecular pathways, posing it as a potential therapeutic target of NAFLD, although more studies in this field are needed.

Ceruletide and Alpha-1 Antitrypsin as a Novel Combination Therapy for Ischemic Stroke.

Ischemic stroke is a primary cause of morbidity and mortality worldwide. Beyond the approved thrombolytic therapies, there is no effective treatment to mitigate its progression. Drug repositioning combinational therapies are becoming promising approaches to identify new uses of existing drugs to synergically target multiple disease-response mechanisms underlying complex pathologies. Here, we used a systems biology-based approach based on artificial intelligence and pattern recognition tools to generate in silico mathematical models mimicking the ischemic stroke pathology. Combinational treatments were acquired by screening these models with more than 5 million two-by-two combinations of drugs. A drug combination (CA) formed by ceruletide and alpha-1 antitrypsin showing a predicted value of neuroprotection of 92% was evaluated for their synergic neuroprotective effects in a mouse pre-clinical stroke model. The administration of both drugs in combination was safe and effective in reducing by 39.42% the infarct volume 24 h after cerebral ischemia. This neuroprotection was not observed when drugs were given individually. Importantly, potential incompatibilities of the drug combination with tPA thrombolysis were discarded in vitro and in vivo by using a mouse thromboembolic stroke model with t-PA-induced reperfusion, revealing an improvement in the forepaw strength 72 h after stroke in CA-treated mice. Finally, we identified the predicted mechanisms of action of ceruletide and alpha-1 antitrypsin and we demonstrated that CA modulates EGFR and ANGPT-1 levels in circulation within the acute phase after stroke. In conclusion, we have identified a promising combinational treatment with neuroprotective effects for the treatment of ischemic stroke.

Benefits of cryopreservation as long-term storage method of encapsulated cardiosphere-derived cells for cardiac therapy: A biomechanical analysis.

Cardiosphere-derived cells (CDCs) encapsulated within alginate-poly-L-lysine-alginate (APA) microcapsules present a promising treatment alternative for myocardial infarction. However, clinical translatability of encapsulated CDCs requires robust long-term preservation of microcapsule and cell stability, since cell culture at 37 °C for long periods prior to patient implantation involve high resource, space and manpower costs, sometimes unaffordable for clinical facilities. Cryopreservation in liquid nitrogen is a well-established procedure to easily store cells with good recovery rate, but its effects on encapsulated cells are understudied. In this work, we assess both the biological response of CDCs and the mechanical stability of microcapsules after long-term (i.e., 60 days) cryopreservation and compare them to encapsulated CDCs cultured at 37 °C. We investigate for the first time the effects of cryopreservation on stiffness and topographical features of microcapsules for cell therapy. Our results show that functionality of encapsulated CDCs is optimum during 7 days at 37 °C, while cryopreservation seems to better guarantee the stability of both CDCs and APA microcapsules properties during longer storage than 15 days. These results point out cryopreservation as a suitable technique for long-term storage of encapsulated cells to be translated from the bench to the clinic.

Force Spectroscopy Imaging and Constriction Assays Reveal the Effects of Graphene Oxide on the Mechanical Properties of Alginate Microcapsules.

Microencapsulation of cells in hydrogel-based porous matrices is an approach that has demonstrated great success in regenerative cell therapy. These microcapsules work by concealing the exogenous cells and materials in a robust biomaterial that prevents their recognition by the immune system. A vast number of formulations and additives are continuously being tested to optimize cell viability and mechanical properties of the hydrogel. Determining the effects of new microcapsule additives is a lengthy process that usually requires extensive in vitro and in vivo testing. In this paper, we developed a workflow using nanoindentation (i.e., indentation with a nanoprobe in an atomic force microscope) and a custom-built microfluidic constriction device to characterize the effect of graphene oxide (GO) on three microcapsule formulations. With our workflow, we determined that GO modifies the microcapsule stiffness and surface properties in a formulation-dependent manner. Our results also suggest, for the first time, that GO alters the conformation of the microcapsule hydrogel and its interaction with subsequent coatings. Overall, our workflow can infer the effects of new additives on microcapsule surfaces. Thus, our workflow can contribute to diminishing the time required for the validation of new microcapsule formulations and accelerate their clinical translation.

In-silico drug repurposing study predicts the combination of pirfenidone and melatonin as a promising candidate therapy to reduce SARS-CoV-2 infection progression and respiratory distress caused by cytokine storm.

From January 2020, COVID-19 is spreading around the world producing serious respiratory symptoms in infected patients that in some cases can be complicated by the severe acute respiratory syndrome, sepsis and septic shock, multiorgan failure, including acute kidney injury and cardiac injury. Cost and time efficient approaches to reduce the burthen of the disease are needed. To find potential COVID-19 treatments among the whole arsenal of existing drugs, we combined system biology and artificial intelligence-based approaches. The drug combination of pirfenidone and melatonin has been identified as a candidate treatment that may contribute to reduce the virus infection. Starting from different drug targets the effect of the drugs converges on human proteins with a known role in SARS-CoV-2 infection cycle. Simultaneously, GUILDify v2.0 web server has been used as an alternative method to corroborate the effect of pirfenidone and melatonin against the infection of SARS-CoV-2. We have also predicted a potential therapeutic effect of the drug combination over the respiratory associated pathology, thus tackling at the same time two important issues in COVID-19. These evidences, together with the fact that from a medical point of view both drugs are considered safe and can be combined with the current standard of care treatments for COVID-19 makes this combination very attractive for treating patients at stage II, non-severe symptomatic patients with the presence of virus and those patients who are at risk of developing severe pulmonary complications.

Aging Increases Hippocampal DUSP2 by a Membrane Cholesterol Loss-Mediated RTK/p38MAPK Activation Mechanism.

Numerous studies suggest that the increased activity of p38MAPK plays an important role in the abnormal immune and inflammatory response observed in the course of neurodegenerative diseases such as Alzheimer's disease. On the other hand, high levels of p38MAPK are present in the brain during normal aging, suggesting the existence of mechanisms that keep the p38MAPK-regulated pro-inflammatory activity within physiological limits. In this study, we show that high p38MAPK activity in the hippocampus of old mice is in part due to the reduction in membrane cholesterol that constitutively occurs in the aging brain. Mechanistically, membrane cholesterol reduction increases p38MAPK activity through the stimulation of a subset of tyrosine kinase receptors (RTKs). In turn, activated p38MAPK increases the expression and activity of the phosphatase DUSP2, which is known to reduce the activity of different MAPKs, including p38MAPK. These results suggest that the loss of membrane cholesterol that constitutively occurs with age takes part in a negative-feedback loop that keeps p38MAPK activity levels within physiological range. Thus, conditions that increase p38MAPK activity such as cellular stressors or that inhibit DUSP2 will amplify inflammatory activity with its consequent deleterious functional changes.

Signaling networks in MS: a systems-based approach to developing new pharmacological therapies.

The pathogenesis of multiple sclerosis (MS) involves alterations to multiple pathways and processes, which represent a significant challenge for developing more-effective therapies. Systems biology approaches that study pathway dysregulation should offer benefits by integrating molecular networks and dynamic models with current biological knowledge for understanding disease heterogeneity and response to therapy. In MS, abnormalities have been identified in several cytokine-signaling pathways, as well as those of other immune receptors. Among the downstream molecules implicated are Jak/Stat, NF-Kb, ERK1/3, p38 or Jun/Fos. Together, these data suggest that MS is likely to be associated with abnormalities in apoptosis/cell death, microglia activation, blood-brain barrier functioning, immune responses, cytokine production, and/or oxidative stress, although which pathways contribute to the cascade of damage and can be modulated remains an open question. While current MS drugs target some of these pathways, others remain untouched. Here, we propose a pragmatic systems analysis approach that involves the large-scale extraction of processes and pathways relevant to MS. These data serve as a scaffold on which computational modeling can be performed to identify disease subgroups based on the contribution of different processes. Such an analysis, targeting these relevant MS-signaling pathways, offers the opportunity to accelerate the development of novel individual or combination therapies.